Rationale and objectives: This study aimed to investigate the prognostic value of preoperative CT scan-derived myocardial biomarkers in patients with severe aortic stenosis (AS) undergoing transcatheter aortic valve replacement (TAVR). Materials and methods: In April 2024, three databases (PubMed, Web of Science and Embase) were searched to identify studies. A random-effects model for meta-analysis was conducted to calculate pooled hazard ratios (HR) and 95% confidence intervals (CI) to assess the prognostic value. The I2 statistic was used to assess heterogeneity. Meta-regression analysis was conducted to appraise which variables yielded a significant impact on the HR of included biomarkers. Results: 11 studies were identified, of which six studies involved 678 patients reporting extracellular volume fraction (ECV), one study involved 300 patients reporting ECV and left ventricular global longitudinal strain (LVGLS), three studies involved 868 patients reporting LVGLS and one study involved 376 patients reporting LVGLS and peak left atrial longitudinal strain (PALS). The endpoints included all-cause mortality, major adverse cardiovascular events (MACE) and a composite outcome of the previous two. The meta-analysis revealed that ECV, whether considered as a dichotomous variable (pooled HR: 3.87, 95% CI: 2.63-5.70, I2 = 0%), or as a continuous variable (pooled HR: 1.12, 95% CI: 1.05-1.19, I2 = 66%), and LVGLS, whether considered as a dichotomous variable (pooled HR: 1.70, 95% CI: 1.30-2.22, I2 = 0%) or a continuous variable (pooled HR: 1.07, 95% CI: 1.04-1.10, I2 = 0%) were all significant predictors for outcomes in patients with severe AS after TAVR. Age, sex, follow-up time and mean pressure gradient had a significant impact on the model of ECV (continuous). Conclusion: The higher CT-derived ECV and impaired LVGLS are able to predict worse outcomes in patients with severe AS who have undergone TAVR.

Introduction: In recent years, the role of pharmacists has undergone significant transformation to become more patient-centered and involved in managing chronic diseases. Nonetheless, it remains unclear whether pharmacist involvement in diabetes management is cost-effective. This study aimed to systematically review the cost-effectiveness and reporting quality in comprehensive economic evaluations of pharmacist management compared to standard care in diabetes. Methods: Eligible studies included cost-effectiveness analyses employing pharmacist professional services as the intervention for diabetes. A literature search was conducted in the bibliographic databases Pubmed, Scopus, China National Knowledge Infrastructure (CNKI), and the International Health Technology Assessment (HTA) database from their inception until July 2023. Two independent reviewers performed title, abstract, full-text screening, and data abstraction and assessed the quality of reporting and methodological approaches using the Consolidated Health Economic Evaluation Reporting Standards (CHEERS 2022) checklists. Results: Twelve studies were identified with an average research quality score of 19.8, including cost-utility (n = 5) and cost-effectiveness (n = 7) analyses, with only four studies rated as high quality. The efficacy data were derived from randomized controlled trials (n = 7), retrospective studies (n = 2), and published literature sources (n = 2). Half of the included studies were conducted in high-income countries, while the other half was in upper-middle and lower-middle-income countries, respectively. Despite significant variations in the cost of pharmacist intervention, consistent findings demonstrate that pharmacist involvement in diabetes management is more cost-effective or even cost-saving than standard care, primarily attributed to better glycemic control, enhanced patient compliance, and reduced risks of medication-related problems. Conclusion: This systematic review substantiates that pharmacist involvement in diabetes management is cost-effective compared with standard care. However, the overall quality of reporting needs to be improved, and high-quality evidence is urgently needed to support healthcare decision-making in pharmacy practice.